When it comes to the information technology industry, you will see that the concept ‘big data’ is making a lot of buzz. You might have heard about this term because a lot of people in the IT industry are making a bigger buzz about it just to impress other people usually without them even knowing what it means exactly. Most companies use this concept as a marketing trick and even utilized out of context. Luckily, you can learn what you can about big data here and then learn more of its being useful in being used as a tool to solve a number of problems.
If you want to learn more about the distances of locations and countries, you need to understand that calculations are carried out by the use of Mathematics and Physics. These two things have made it very much possible for the great achievements that are being used across technologies as people live their lives on a daily basis. What remains as a challenge will then be getting the measurements using data that is not static. The term non-static is employed among objects and things that get to constantly change in real time at volumes and rates that are bigger than anyone can imagine. Utilizing some computers seems to be the only viable option in being able to process such crucial date.
According to IBM data scientists, big data can be broken down into four aspects, they are called veracity, velocity, variety, and volume. And yet, these four aspects are not just what big data is all about. What you will see after are the identifying characteristics that make big data what it is now and what it entails.
One of the ways to find out about your data being really called big data is to take a look at its volume and analyze its sized in association with potential and value if it is really to be called big data. With the classification of variety, this is the identification where your data is a part of in terms of category that is being determined by the data analysts. This aids in the people who are the ones assigned in associating the data and then analyzing them to the best of their intentions. Such data has been proven to be very beneficial among these people for use to their own advantage in more ways than one. Knowing how fast the data will be processed and generated if it is useful enough is also the doing of velocity. The aspect of variability is also crucial to determining what problem data analysts might be coming across. And finally, you have veracity that identifies the captured data quality. For accurate assessment of your big data quality, it will have to depend on how much veracity your source data has.
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